Quantifying differential gene connectivity between disease states for objective identification of disease-relevant genes

<p>Abstract</p> <p>Background</p> <p>Network modeling of whole transcriptome expression data enables characterization of complex epistatic (gene-gene) interactions that underlie cellular functions. Though numerous methods have been proposed and successfully implemented to develop these networks, there are no formal methods for comparing differences in network connectivity patterns as a function of phenotypic trait.</p> <p>Results</p> <p>Here we describe a novel approach for quantifying the differences in gene-gene connectivity patterns across disease states based on Graphical Gaussian Models (GGMs). We compare the posterior probabilities of connectivity for each gene pair across two disease states, expressed as a posterior odds-ratio (postOR) for each pair, which can be used to identify network components most relevant to disease status. The method can also be generalized to model differential gene connectivity patterns within previously defined gene sets, gene networks and pathways. We demonstrate that the GGM method reliably detects differences in network connectivity patterns in datasets of varying sample size. Applying this method to two independent breast cancer expression data sets, we identified numerous reproducible differences in network connectivity across histological grades of breast cancer, including several published gene sets and pathways. Most notably, our model identified two gene hubs (MMP12 and CXCL13) that each exhibited differential connectivity to more than 30 transcripts in both datasets. Both genes have been previously implicated in breast cancer pathobiology, but themselves are not differentially expressed by histologic grade in either dataset, and would thus have not been identified using traditional differential gene expression testing approaches. In addition, 16 curated gene sets demonstrated significant differential connectivity in both data sets, including the matrix metalloproteinases, PPAR alpha sequence targets, and the PUFA synthesis pathway.</p> <p>Conclusions</p> <p>Our results suggest that GGM can be used to formally evaluate differences in global interactome connectivity across disease states, and can serve as a powerful tool for exploring the molecular events that contribute to disease at a systems level.</p

Power enhancement via multivariate outlier testing with gene expression arrays

Motivation: As the use of microarrays in human studies continues to increase, stringent quality assurance is necessary to ensure accurate experimental interpretation. We present a formal approach for microarray quality assessment that is based on dimension reduction of established measures of signal and noise components of expression followed by parametric multivariate outlier testing

Cell Culture Modeling to Test Therapies Against Hyperglycemia-Mediated Oxidative Stress and Injury

The concept that oxidative stress is a key mediator of nerve injury in diabetes has led us to design therapies that target oxidative stress mechanisms. Using an in vitro model of glucose-treated dorsal root ganglion (DRG) neurons in culture, we can examine both free radical generation, using fluorimetric probes for reactive oxygen species, and cell death via the TUNEL assay. The cell culture system is scaled down to a 96-well plate format, and so is well suited to high-throughput screening. In the present study, we test the ability of three drugs, nicotinamide, allopurinol, and α-lipoic acid, alone and in combination to prevent DRG neuron oxidative stress and cell death. This combination of drugs is currently in clinical trial in type 1 diabetic patients. We demonstrate independent effects on oxidative stress and neuronal survival for the three drugs, and neuronal protection using the three drugs in combination. The data strengthen the rationale for the current clinical trial. In addition, we describe an effective tool for rapid preclinical testing of novel therapies against diabetic neuropathy. Antioxid. Redox Signal. 7, 1494–1506.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63115/1/ars.2005.7.1494.pd

The Spitzer Warm Mission Science Prospects

After exhaustion of its cryogen, the Spitzer Space telescope will still have a fully functioning two-channel mid-IR camera that will have sensitivities better than any other ground or space-based telescopes until the launch of JWST. This document provides a description of the expected capabilities of Spitzer during its warm mission phase, and provides brief descriptions of several possible very large science programs that could be conducted. This information is intended to serve as input to a wide ranging discussion of the warm mission science, leading up to the Warm Mission Workshop in June 2007

Software for Computing and Annotating Genomic Ranges

We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization

Immunogenicity of unprocessed and photooxidized bovine and human osteochondral grafts in collagen-sensitive mice

BACKGROUND: Autologous and allogeneic osteochondral grafts have been used to repair damaged or diseased cartilage. There are drawbacks to both of these methods, however. Another possible source for osteochondral grafting is photooxidized xenograft scaffolds. The purpose of this study was to evaluate the adaptive immune response to unprocessed and photooxidized xenogeneic osteochondral grafts in a collagen-sensitive mouse model. METHODS: Unprocessed and photooxidized bovine and human osteochondral grafts were used. The grafts were implanted subcutaneously in collagen-sensitive DBA/1LacJ mice for four or twelve weeks. ELISPOT assays were conducted with spleen cells to evaluate the number of collagen-specific T cells that produce IL-2, IL-4, IL-5 or IFN-γ. Serum was collected and ELISA assays were performed to determine the titers of collagen-specific and total IgG, IgG1, IgG2a, or IgM antibodies. Histology was conducted on the retrieved osteochondral grafts. RESULTS: Results indicated that, with respect to adaptive T cell immunity, the photooxidized bovine grafts, unprocessed human grafts and photooxidized human grafts did not induce a significant response to collagen. The unprocessed bovine grafts, however, were slightly more immunogenic, inducing a weak immune response. With respect to antibody production, the bovine grafts were less immunogenic than the human grafts. Bovine collagen-specific IgG antibodies were not induced by these grafts, but production of IgM after twelve weeks was observed with both the unprocessed and photooxidized bovine grafts. In contrast, photooxidized human osteochondral grafts induced IgG1 and IgG2a antibodies, while the unprocessed human grafts did not. Pre-existing human collagen-specific IgM antibodies were present in all mice, including sham-operated negative controls that did not receive an implant. Histological analysis revealed some degree of fibrous encapsulation and inflammatory infiltrations in both bovine and human implants, whether unprocessed or photooxidized. CONCLUSION: Both bovine and human cartilage grafts showed weak, but clear immunogenicity in the DBA/1LacJ mice, indicating that immunogenic collagen was still contained in the grafts, even after cleaning and photooxidation. The process of photooxidation is still important in osteochondral grafting, since it stabilizes the surface of the cartilage by cross-linking the collagen fibers, and allows for immediate load bearing and joint resurfacing

Loss of N-WASP drives early progression in an Apc model of intestinal tumourigenesis

N‐WASP (WASL) is a widely expressed cytoskeletal signalling and scaffold protein also implicated in regulation of Wnt signalling and homeostatic maintenance of skin epithelial architecture. N‐WASP mediates invasion of cancer cells in vitro and its depletion reduces invasion and metastatic dissemination of breast cancer. Given this role in cancer invasion and universal expression in the gastrointestinal tract, we explored a role for N‐WASP in the initiation and progression of colorectal cancer. While deletion of N‐wasp is not detectably harmful in the murine intestinal tract, numbers of Paneth cells increased, indicating potential changes in the stem cell niche and migration up the crypt‐villus axis was enhanced. Loss of N‐wasp promoted adenoma formation in an adenomatous polyposis coli (Apc) deletion model of intestinal tumourigenesis. Thus, we establish a tumour suppressive role of N‐WASP in early intestinal carcinogenesis despite its later pro‐invasive role in other cancers. Our study highlights that while the actin cytoskeletal machinery promotes invasion of cancer cells, it also maintains normal epithelial tissue function and thus may have tumour suppressive roles in pre‐neoplastic tissues

Platform dependence of inference on gene-wise and gene-set involvement in human lung development

<p>Abstract</p> <p>Background</p> <p>With the recent development of microarray technologies, the comparability of gene expression data obtained from different platforms poses an important problem. We evaluated two widely used platforms, Affymetrix U133 Plus 2.0 and the Illumina HumanRef-8 v2 Expression Bead Chips, for comparability in a biological system in which changes may be subtle, namely fetal lung tissue as a function of gestational age.</p> <p>Results</p> <p>We performed the comparison via sequence-based probe matching between the two platforms. "Significance grouping" was defined as a measure of comparability. Using both expression correlation and significance grouping as measures of comparability, we demonstrated that despite overall cross-platform differences at the single gene level, increased correlation between the two platforms was found in genes with higher expression level, higher probe overlap, and lower p-value. We also demonstrated that biological function as determined via KEGG pathways or GO categories is more consistent across platforms than single gene analysis.</p> <p>Conclusion</p> <p>We conclude that while the comparability of the platforms at the single gene level may be increased by increasing sample size, they are highly comparable ontologically even for subtle differences in a relatively small sample size. Biologically relevant inference should therefore be reproducible across laboratories using different platforms.</p